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Compare Elementary Data and Monte Carlo 
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At a Glance
Market Segments
Mid-Market (55.6% of reviews)
Enterprise (51.2% of reviews)
Entry-Level Pricing
No pricing available
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Elementary Data
Star Rating
(18)4.5 out of 5
Market Segments
Mid-Market (55.6% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about Elementary DataMonte Carlo
Star Rating
(462)4.4 out of 5
Market Segments
Enterprise (51.2% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Us
Browse all 3 pricing plansSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Monte Carlo excels in data quality monitoring with a score of 8.9, while Elementary Data closely follows with 8.8. Reviewers mention that Monte Carlo's robust monitoring features help in identifying data issues proactively, which is crucial for maintaining data integrity.
- Reviewers mention that Monte Carlo's real-time analytics capabilities score 7.3, significantly outperforming Elementary Data's 5.5. Users say that the ability to analyze data in real-time is a game-changer for decision-making processes, making Monte Carlo a preferred choice for businesses needing immediate insights.
- G2 users highlight that Monte Carlo's quality of support is rated at 9.1, slightly higher than Elementary Data's 9.0. Users report that the responsiveness and expertise of Monte Carlo's support team have been instrumental in resolving issues quickly, enhancing the overall user experience.
- Users on G2 mention that Monte Carlo offers superior anomaly identification features with a score of 8.8 compared to Elementary Data's 8.7. Reviewers say that this functionality is vital for detecting irregularities in data flows, allowing teams to act swiftly and mitigate risks.
- Reviewers mention that while both products provide automated workflows, Monte Carlo's score of 7.8 is slightly lower than Elementary Data's 8.3. Users report that Elementary Data's automation features are more intuitive, making it easier for teams to set up and manage workflows without extensive training.
- Users say that Monte Carlo shines in its product direction, receiving a positive score of 9.2, while Elementary Data boasts a perfect 10.0. Reviewers mention that the clear roadmap and commitment to innovation from Elementary Data give them confidence in the product's future development.
Pricing
Entry-Level Pricing
Elementary Data
No pricing availableMonte Carlo
Start
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All you need to make data reliable for one team
- Monitoring for Data Warehouse, Business Intelligence, ETL
- Incident triaging, troubleshooting and root cause analysis
- Lineage
Free Trial
Elementary Data
No trial information availableMonte Carlo
No trial information availableRatings
Meets Requirements
8.5
16
8.3
430
Ease of Use
8.5
18
8.2
437
Ease of Setup
8.7
17
8.2
303
Ease of Admin
8.9
6
8.5
160
Quality of Support
9.2
14
9.0
386
Has the product been a good partner in doing business?
8.7
5
9.3
163
Product Direction (% positive)
10.0
16
8.9
426
Features by Category
Functionality
Not enough data
9.0
257
Not enough data
8.8
258
Not enough data
7.8
235
Not enough data
8.3
244
Not enough data
7.7
239
Not enough data
7.4
241
Agentic AI - Database Monitoring
Not enough data
7.1
13
Not enough data
6.9
13
Not enough data
6.9
13
Not enough data
7.1
13
Not enough data
6.8
12
Not enough data
6.5
13
Not enough data
7.1
13
Data Management
Not enough data
8.5
49
Not enough data
8.5
45
Not enough data
8.6
49
Not enough data
7.9
47
Agentic AI - DataOps Platforms
Not enough data
7.2
6
Not enough data
6.0
5
Not enough data
6.3
5
Not enough data
6.3
5
Not enough data
6.3
5
Analytics
Not enough data
7.8
48
Not enough data
7.7
46
Monitoring and Management
Not enough data
9.2
53
Not enough data
7.6
46
Cloud Deployment
Not enough data
7.4
42
Not enough data
7.0
40
Generative AI
Not enough data
6.2
33
Not enough data
6.1
33
Functionality
4.9
13
7.3
287
9.1
13
8.8
318
8.6
14
8.1
291
8.1
13
8.0
295
Management
9.0
13
8.7
313
8.7
13
7.8
284
7.9
14
8.3
307
7.8
13
8.0
301
7.8
13
8.1
307
Generative AI
6.3
5
5.8
227
Agentic AI - Data Observability
Not enough data
6.1
27
Not enough data
6.2
27
Not enough data
6.7
27
Not enough data
6.4
26
Not enough data
6.7
29
Functionality
9.0
7
8.1
184
4.3
7
6.4
171
4.3
7
6.6
166
4.5
7
6.0
161
7.9
7
6.4
162
Management
9.0
8
7.2
167
8.1
6
7.5
167
9.7
6
7.9
165
9.3
7
7.4
172
7.5
6
7.5
167
Generative AI
1.1
6
5.2
142
1.1
6
5.3
142
Categories
Categories
Shared Categories
Elementary Data and Monte Carlo are categorized as Data Observability, Data Quality, DataOps Platforms, and Database Monitoring
Unique Categories
Elementary Data has no unique categories
Monte Carlo has no unique categories
Reviews
Reviewers' Company Size
Elementary Data
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Monte Carlo
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Financial Services
22.2%
Retail
11.1%
Entertainment
11.1%
Computer Software
11.1%
Consulting
5.6%
Other
38.9%
Financial Services
14.2%
Information Technology and Services
10.9%
Computer Software
10.6%
Marketing and Advertising
3.8%
Manufacturing
3.5%
Other
57.0%
Discussions
Elementary Data has no discussions with answers
What is Monte Carlo software?
1 Comment
MV
Monte Carlo is a fully automated, end-to-end data observability platform that helps data engineering teams reduce time to detection and resolution for data...Read more
Monte Carlo has no more discussions with answers
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